Jenna M. Bartley

Metabolic characteristics of keto-adapted ultra-endurance runners.

BACKGROUND Many successful ultra-endurance athletes have switched from a high-carbohydrate to a low-carbohydrate diet, but they have not previously been studied to determine the extent of metabolic adaptations. METHODS Twenty elite ultra-marathoners and ironman distance triathletes performed a maximal graded exercise test and a 180 min submaximal run at 64% VO2max on a treadmill to determine metabolic responses. One group habitually consumed a traditional high-carbohydrate (HC: n=10, %carbohydrate:protein:fat=59:14:25) diet, and the other a low-carbohydrate (LC; n=10, 10:19:70) diet for an average of 20 months (range 9 to 36 months). RESULTS Peak fat oxidation was 2.3-fold higher in the LC group (1.54±0.18 vs 0.67±0.14 g/min; P=0.000) and it occurred at a higher percentage of VO2max (70.3±6.3 vs 54.9±7.8%; P=0.000). Mean fat oxidation during submaximal exercise was 59% higher in the LC group (1.21±0.02 vs 0.76±0.11 g/min; P=0.000) corresponding to a greater relative contribution of fat (88±2 vs 56±8%; P=0.000). Despite these marked differences in fuel use between LC and HC athletes, there were no significant differences in resting muscle glycogen and the level of depletion after 180 min of running (-64% from pre-exercise) and 120 min of recovery (-36% from pre-exercise). CONCLUSION Compared to highly trained ultra-endurance athletes consuming an HC diet, long-term keto-adaptation results in extraordinarily high rates of fat oxidation, whereas muscle glycogen utilization and repletion patterns during and after a 3 hour run are similar.

Report: NIA Workshop on Measures of Physiologic Resiliencies in Human Aging

Background/Objectives Resilience, the ability to resist or recover from adverse effects of a stressor, is of widespread interest in social, psychologic, biologic, and medical research and particularly salient as the capacity to respond to stressors becomes diminished with aging. To date, research on human resilience responses to and factors influencing these responses has been limited. Methods The National Institute on Aging convened a workshop in August 2015 on needs for research to improve measures to predict and assess resilience in human aging. Effects of aging-related factors in impairing homeostatic responses were developed from examples illustrating multiple determinants of clinical resilience outcomes. Research directions were identified by workshop participants. Results Research needs identified included expanded uses of clinical data and specimens in predicting or assessing resilience, and contributions from epidemiological studies in identifying long-term predictors. Better measures, including simulation tests, are needed to assess resilience and its determinants. Mechanistic studies should include exploration of influences of biologic aging processes on human resiliencies. Important resource and infrastructure needs include consensus phenotype definitions of specific resiliencies, capacity to link epidemiological and clinical resilience data, sensor technology to capture responses to stressors, better laboratory animal models of human resiliencies, and new analytic methods to understand the effects of multiple determinants of stress responses. Conclusions Extending the focus of care and research to improving the capacity to respond to stressors could benefit older adults in promoting a healthier life span.

Aging augments the impact of influenza respiratory tract infection on mobility impairments, muscle-localized inflammation, and muscle atrophy

Although the influenza virus only infects the respiratory system, myalgias are commonly experienced during infection. In addition to a greater risk of hospitalization and death, older adults are more likely to develop disability following influenza infection; however, this relationship is understudied. We hypothesized that upon challenge with influenza, aging would be associated with functional impairments, as well as upregulation of skeletal muscle inflammatory and atrophy genes. Infected young and aged mice demonstrated decreased mobility and altered gait kinetics. These declines were more prominent in hind limbs and in aged mice. Skeletal muscle expression of genes involved in inflammation, as well as muscle atrophy and proteolysis, increased during influenza infection with an elevated and prolonged peak in aged mice. Infection also decreased expression of positive regulators of muscle mass and myogenesis components to a greater degree in aged mice. Gene expression correlated to influenza-induced body mass loss, although evidence did not support direct muscle infection. Overall, influenza leads to mobility impairments with induction of inflammatory and muscle degradation genes and downregulation of positive regulators of muscle. These effects are augmented and prolonged with aging, providing a molecular link between influenza infection, decreased resilience and increased risk of disability in the elderly.

Impact of Age, Caloric Restriction, and Influenza Infection on Mouse Gut Microbiome: An Exploratory Study of the Role of Age-Related Microbiome Changes on Influenza Responses

Immunosenescence refers to age-related declines in the capacity to respond to infections such as influenza (flu). Caloric restriction represents a known strategy to slow many aging processes, including those involving the immune system. More recently, some changes in the microbiome have been described with aging, while the gut microbiome appears to influence responses to flu vaccination and infection. With these considerations in mind, we used a well-established mouse model of flu infection to explore the impact of flu infection, aging, and caloric restriction on the gut microbiome. Young, middle-aged, and aged caloric restricted (CR) and ad lib fed (AL) mice were examined after a sublethal flu infection. All mice lost 10–20% body weight and, as expected for these early time points, losses were similar at different ages and between diet groups. Cytokine and chemokine levels were also similar with the notable exception of IL-1α, which rose more than fivefold in aged AL mouse serum, while it remained unchanged in aged CR serum. Fecal microbiome phyla abundance profiles were similar in young, middle-aged, and aged AL mice at baseline and at 4 days post flu infection, while increases in Proteobacteria were evident at 7 days post flu infection in all three age groups. CR mice, compared to AL mice in each age group, had increased abundance of Proteobacteria and Verrucomicrobia at all time points. Interestingly, principal coordinate analysis determined that diet exerts a greater effect on the microbiome than age or flu infection. Percentage body weight loss correlated with the relative abundance of Proteobacteria regardless of age, suggesting flu pathogenicity is related to Proteobacteria abundance. Further, several microbial Operational Taxonomic Units from the Bacteroidetes phyla correlated with serum chemokine/cytokines regardless of both diet and age suggesting an interplay between flu-induced systemic inflammation and gut microbiota. These exploratory studies highlight the impact of caloric restriction on fecal microbiome in both young and aged animals, as well as the many complex relationships between flu responses and gut microbiota. Thus, these preliminary studies provide the necessary groundwork to examine how gut microbiota alterations may be leveraged to influence declining immune responses with aging.

The impact of aging on CD4+ T cell responses to influenza infection

CD4+ T cells are important for generating high quality and robust immune responses to influenza infection. Immunosenescence that occurs with aging, however, compromises the ability of CD4+ T cells to differentiate into functional subsets resulting in a multitude of dysregulated responses namely, delayed viral clearance and prolonged inflammation leading to increased pathology. Current research employing animal models and human subjects has provided new insights into the description and mechanisms of age-related CD4+ T cell changes. In this review, we will discuss the consequences of aging on CD4+ T cell differentiation and function and how this influences the initial CD4+ T cell effector responses to influenza infection. Understanding these age-related alterations will aid in the pharmacological development of therapeutic treatments and improved vaccination strategies for the vulnerable elderly population.

Muscle Ultrasound As a Link to Muscle Quality and Frailty in the Clinic

Sarcopenia, or age-related decline in skeletal muscle mass and strength, is a major public health concern, affecting up to 29% of community-dwelling older adults. This decline is commonly coupled with declines in muscle function and performance, a major component of the frailty phenotype. Multiple components of the frailty phenotype that Fried and colleagues described (unintentional weight loss, weakness, poor endurance and energy, slow gait speed, low physical activity) involve muscle dysfunction at their core. Because of the overlapping paradigms, sarcopenia and frailty are commonly studied in parallel and often present concurrently in the clinic. Frailty denotes a syndrome with poor ability to respond to stressors and maintain homeostasis, rendering the person vulnerable to a variety of adverse outcomes. Sarcopenia and frailty are independent risk factors for negative health outcomes, including falls, fractures, disability, and mortality. Thus, being able to identify who is at greater risk of these adverse events is invaluable. Despite these implications, assessment of sarcopenia and frailty is not straightforward and currently lacks a true criterion standard. Research has highlighted the importance of muscle quality rather than muscle mass alone in evaluating muscle performance and sarcopenia; the decline in muscle mass alone does not fully explain the decrease in strength and power with age, and muscle quality may be a better predictor of health status and functional limitations. Muscle quality refers to the muscle’s functional capacity, including force, contraction ability, metabolism, and other functions. Aging greatly affects muscle quality, with impaired protein synthesis, slower contraction speed, altered neuromuscular activation, and greater fatty infiltration (reviewed elsewhere). Many methods are available to measure muscle mass and muscle quality, although each comes with limitations, and finding a true biomarker of sarcopenia and frailty has proven to be extremely difficult. Some approaches to measuring muscle quality focus on muscle composition, and others reflect strength relative to muscle mass. Magnetic resonance imaging (MRI) and computed tomography (CT) can reliably estimate muscle mass and quantify fat infiltration into muscle, but they are not readily available in all clinical settings and are relatively expensive. Dual-energy X-ray absorptiometry (DXA) is less expensive and technically simpler to use but offers no information on muscle composition. In many research studies, muscle quality is assessed using a measurement of strength or power normalized to muscle mass using DXA, CT, or MRI. Although useful, some tests of strength and power are sex dependent, and comorbidities can confound them. The normalized measures of muscle quality also depend on assumptions about muscle volume derived from two-dimensional images. Physical performance assessments such as the Short Physical Performance Battery (SPPB), grip strength, and gait speed can provide some perspective on the functional consequences of poor muscle quality but do not directly measure strength, mass, or composition. Thus, although there is no shortage of assessment tools available, there is no consensus on the most-appropriate measures and ways to use them to classify sarcopenia and frailty. In this issue of the Journal of American Geriatrics Society, Miron Mombiela and colleagues present preliminary validation of a practical, low-cost assessment tool to evaluate muscle quality in the context of frailty in the clinic. Focusing on the importance of muscle quality as reflected by muscle composition rather than as a strengthto-mass ratio, Miron Mombiela and colleagues examine the relationship between muscle quality assessed by ultrasound echointensity (EI) and frailty status. Briefly, B-mode ultrasound with a high-resolution transducer coupled with grayscale analysis allows quantification of mean pixel intensity. Others have shown the negative association between EI and muscle strength, with greater fat infiltration within the muscle increasing EI values and being associated with poorer muscle strength, but no one had previously assessed relationships with clinically relevant markers of frailty. The authors confirm the previous reported relationships and further these findings by showing the utility of EI measurements according to frailty status. The authors show that EI values are significantly higher in prefrail and frail individuals. Adding support to their findings, EI was also associated with muscle strength, muscle thickness, and quality of life—markers with strong relationships with frailty status in previous research. Although these findings are informative, further work is needed before this technique can be translated to the clinical setting. The study was performed with a small sample size and was cross-sectional. Larger, longitudinal studies in diverse populations are needed to determine whether baseline EI status predicts future health and functional status, whether changes over time in EI are meaningful, and whether interventions that improve muscle This editorial comments on the article by Borras et al.